Investigating Relationships Between The Backdrop of Provincial Economic Volatility and Wider Mental Health in Alberta:

Introduction and Motivation

Our proposed digital exploration will analyze the linkage between economic factors and mental health trends within the wider Alberta population. The Mental Health Commission of Canada conducted an economic review in 2011 and provided an estimate of the impact of mental health illnesses on lost productivity due to absenteeism, presenteeism (present but less than fully productive at work) and turnover; in 2011 alone, the cost to the economy was 6.3 billion. This value is projected to rise to 16 billion in 2041. In any given year, 1 in 5 Canadians experiences a mental illness or addiction problem and by the time Canadians reach 40 years of age, 1 in 2 have, or have had, a mental illness. This means that more than 6.7 million people in Canada are living with a mental health problem or illness today. That is 19.8% of Canada’s population in any given year. It is likely that because there is stigma attached to harbouring a mental health diagnosis, that reported metrics are understated. According to the World Health Organization (WHO) the incidence of mental illness is expected to rise as economic drivers become increasingly dynamic, and the “gig economy” becomes more commonplace. The collective provincial population would benefit vastly from applied data analytics in order to address the compounding mental health crisis that is ongoing within the province. It is possible that in the future, applied analytics will be able to guide policy makers to utilize provincially budgeted resources in a more targeted and efficient manner.

On an aggregate level, it is well documented that the relationship between economic inequality and mental health exists, but despite this, a reductionist biomedical model assessing mental health on an individual and physiological basis has persisted within the academic medical community. This has limited the ability of corporate entities and policy makers to address inequalities within the mental health sphere. Another driving factor of mental health inequality has been economic volatility. The province of Alberta has experienced significant economic hardship following the collapse of Western Canadian Select (WCS) oil prices and NOVA/AECO-C gas prices in 2014/2015. Since that time, the energy market never fully recovered. The new commodity price environment also spurred a wider thematic global investment shift away from the energy industry and mounted pressure on corporate entities to support ESG driven narratives.

We knew going into the analysis that medically rooted data is safeguarded by medical ethics boards, and it would therefore more challenging to locate granular medical datasets. We hypothesized that given that economic data tends to be standardized over a wide time window, it would be prudent to conclude that our mental health datasets would be scope limiting. We were in fact correct. It was challenging to get standardized medical data over a long-time horizon, and thus challenging to uncover trends, but we did find patterns within our analysis. Our core dataset which we utilized alongside Alberta economic data came from the Canadian Community Health Survey (CCHS). Each year the CCHS works alongside Statistics Canada to gather health-related data at provincial levels of geography. The data lent itself to a subgroup analysis that we chose to look at alongside Alberta economic data that was available on the Alberta Economic Dashboard. While The Statistics Canada Database served as our core dataset, we also intended to utilize the Mental Health and Addictions Hospitalizations in Canada Supplementary Tables which are released annually by the Canadian Institute for Health Information (CIHI). Within the CIHI data, we utilized the ‘discharges’ and ‘discharge rates’ for mental health disorders, the data was segregated by province/territory. One hardship we came across while conducting our analysis with the CIHI data was that it was only standardized and reported consistently back to 2017. There are no aggregated datasets on the CIHI database, instead there is a report uploaded annually. This created extra wranging work and left us to work with a shorter timeframe. Despite this we still came to interesting conclusions that answered our original questions.

Guiding Questions

Our analysis will look to capture the essence of economic reality which exists within municipalities and the wider province, and overlay that theme with mental health related data. As a way of proceeding, we will clearly lay out our three guiding questions as follows:

  • Is there an identifiable relationship between the dynamic economic situation of the province and the wider mental health trend within Alberta?
  • Which subpopulations have been the most adversely affected by the economic volatility in Alberta within the last decade?
  • What have been the trends in more granular hospital-based mental health data, and do those findings relate to the wider economic analysis and subgroup analysis?